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sts.components.contact.mr.placeholder Sebastian Webel
Mr. Sebastian Webel

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Pictures of the Future
The Magazine for Research and Innovation
 

The Future of Manufacturing

Building Turbines in the Virtual World

Before a component is produced for the first time, programmers at Siemens' gas turbine plant in Berlin simulate all of the steps involved in producing it to ensure that manufacturing will be problem-free and that no collisions involving the workpiece and nearby machines will occur.

New, digital processes have enabled Siemens to increase the utilization of its machine tool capacity by ten percent and reduce the production time for gas turbine burner components by three weeks. In the future, these processes could also be used for drive technology, wind power, and electric motors.

Regardless of whether a manufacturer produces electronic systems, vehicles, or gas turbines, the aim is to steadily shorten throughput times and make manufacturing more efficient while raising quality standards. Manufacturing processes based on digital information provide new possibilities in this regard, because the huge amounts of data they generate can be analyzed to optimize production. This is as true for small-batch manufacturing as it is for mass production because both benefit from this process of data streamlining through shorter time to market and improved quality.

Sebastian Neubert (right) explains how a development program saves all of the relevant product information (e.g. the tolerances of drill holes) in a 3D CAD model of a turbine component.

From Digital Twins to Digital Manufacturing

The creation of a comprehensive chain of 3D computer-aided design (CAD) models is of crucial importance for manufacturing processes based on digital information, says Peter Robl, a digital manufacturing expert at Siemens’ central research unit, Corporate Technology (CT). “Such models contain all of the relevant information about a component, such as its design-related dimensions and tolerances, the designers’ know-how, materials data, and the mechanical properties of the parts provided by suppliers,” he says. According to Robl, these models can also incorporate production process data. What’s more, the models can continue to capture information about a part or product throughout an object’s life cycle. Such information can include, for instance, data covering changing surface qualities, possible deviations discovered during inspections, and information about wear and tear that is supplied by service technicians. This concentrated mass of data creates a lifelong digital twin that can, in turn, be subjected to data analytics and be used to improve subsequent versions of the object.  

3D CAD models enabled experts to greatly reduce the throughput time of each component — from eight weeks to five.

Seamlessly Linking Models

Although simulation technology has become increasingly sophisticated, much work remains to be done before a product’s digital twin can be used to full advantage in a digital industrial ecosystem. Robl points out, for instance, that the associated Siemens software packages — from CAD and computer-aided manufacturing (CAM) to capability maturity models (CMM) still need standardized administrative methods to link them. To date, 3D models in the process chain still need to be converted to two-dimensional models at some points, and machine tools may even have to be programmed manually. “It won’t be possible to create a truly comprehensive 3D data model for the virtual twin until everyone involved in a manufacturing process — the people, the machines, and the programs — has access to all the data and changes are made synchronously in all data packets,” says Robl. That’s why Robl and his team are developing a systematic framework for modeling and managing data. The framework is designed to interlink all 2D and 3D models as well as associated machine tool data and the information provided by suppliers and service staff.

The measuring program for this turbine component was created on the basis of a 3D CAD model from the development department and completes the process chain in production.

Product in a File

In practical terms, this concept, once fully realized, will obviate the need for converting 3D models into two-dimensional models. It will also mean that machine operators will be able to program machine tools offline and use simulations to check the quality of the associated machine programs. They could therefore do this work in an office instead of blocking the use of machines in factories. This would result in higher machine utilization times and fewer errors. Moreover, service specialists would be able to access all of a product’s data in a structured manner and compare its observed wear and tear with its original condition, thus supporting increasingly accurate estimates of its service life.

Digital Manufacturing of Entire Gas Turbines

Sebastian Neubert, a project manager at the Berlin manufacturing development unit of Siemens Power and Gas (PG), is working together with design specialists and experts from Corporate Technology to adapt a comprehensive chain of 3D CAD models for the entire gas turbine production process and to establish comprehensive chains of data. He describes the advantages of such a model as follows: “The burner components for our new generation of gas turbines are the first parts for which we have created comprehensive 3D CAD models for the manufacturing process. These models have shortened the throughput time for each component from eight weeks to five and increased the utilization of machine tool capacity by ten percent.”

Bernhard Wegner, who heads the Berlin-based design team, adds: “The new 3D CAD modeling methods and their associated administrative tools provide us with an important shortcut to the product and reduce the time needed to proceed from the development stage to production by as much as three months. Moreover, these improvements enable us to contribute our know-how regarding manufacturing processes and techniques to a product’s development from the very start in order to improve quality and at the same time reduce costs.”

In an associated achievement, an in-depth analysis and correlation of previously unused data enabled Siemens Corporate Technology researchers to improve the evaluation of the gas flow during the operation of a gas turbine burner. As a result, the researchers were able to dispense with a laborious measurement process, thus accelerating the evaluation throughput time by 20 percent.

As the next step in modeling the entire gas turbine production process, Siemens researchers plan to create a model of a turbine blade that is so data rich that associated machine tool programming can be derived directly from it. The ultimate aim is to gradually introduce this new process chain strategy for all of a gas turbine’s key components. In addition, CT experts want to transfer this digital production concept to other areas, such as drive technologies, wind power, electric motors, and the additive manufacturing of components.

Fenna Bleyl